class_docstr: Class to imitate gensim's KeyedVectors, but instead getting the vectors from the memory,
  the vectors will be retrieved from a redis db.
  Based on https://engineering.talentpair.com/serving-word-vectors-
  for-distributed-computations-c5065cbaa02f
class_docstr_tok: ["Class","to","imitate","gensim","'s","KeyedVectors",",","but","instead","getting","the","vectors","from","the","memory",",","the","vectors","will","be","retrieved","from","a","redis","db",".","Based","on","https",":","\/\/engineering.talentpair.com\/serving-word-vectors-","for-distributed-computations-c5065cbaa02f"]
docstr: Indicates whether the key exists.
docstr_tok: ["Indicates","whether","the","key","exists","."]
code: def exists(self):
      """
      Indicates whether the key exists.
      """
      return bool(self._redis.exists(self.key))
  
file_path: textpipe/textpipe/wrappers.py
imports: import pickle
  from functools import lru_cache
  from urllib.parse import urlparse
  import numpy
  from gensim.models.keyedvectors import KeyedVectors
  from redis import Redis
  from redis.exceptions import RedisError
  from tqdm import tqdm
label_desc: Use image node_id 6 for calling the RedisKeyedVectors obj's underlying member method code with example usage: obj.exists() and returns: bool